High-throughput sequencing and genomes
2026-01-29
Sequencing technology development timeline
Modified after Pereira, Oliveira, and Sousa (2020)
Sequencing technology development timeline
Modified after Pereira, Oliveira, and Sousa (2020)
Sanger sequencing
Sequences a single, typically PCR-amplified, short-ish (≤900 bp) DNA fragment at a time.
Sequencing is performed by synthesizing a new DNA strand with fluorescently-labeled nucleotides, using a different color for each base (A, C, G, T).
The final result is a chromatogram that can be “base-called”:
The entire human genome (3 Gbp) was sequenced with Sanger technology!
Anyone want to guess how much this may have cost?
Sequencing cost through time
https://www.genome.gov/about-genomics/fact-sheets/Sequencing-Human-Genome-cost
Omics
Looking at the bigger picture first, HTS produces data that underlies several of these main “omics” approaches:
Copyright ThermoFisher
Error rates
Currently, no sequencing technology is error-free: the sequenced read may differ from the actual DNA sequence it came from.
- The read can have base-calling errors, missing bases, or extra bases
- When the base calling software is not confident, it can also return
Ns (= undetermined)
When you receive HTS reads, base calls have typically been made already.
Every base call is accompanied by a quality score, representing the estimated error probability.
Correcting sequencing errors
To overcome sequencing errors, every base can be sequenced multiple times –
i.e., obtaining a “depth of coverage” greater than 1:
Typical depths of coverage are ~50-100x for genome assembly and 10-30x for “resequencing” (!)
Which natural phenomenon might complicate this effort?
Genetic variation among and (for diploid organisms) within individualsIllumina (short-read HTS / NGS)
100-300 bp reads with 0.1-0.2% error rates
More reads, lower per-base cost, and generally lower error rates than long-read sequencing.
- Machines differ in throughput, read length, cost per Gb:
Libraries and library prep
In a HTS context, a “library” is a collection of DNA fragments ready for sequencing.
In Illumina libraries, these fragments number in the millions or billions and are often simply randomly generated from input such as genomic DNA:
An overview of the library prep procedure. This is typically done for you by a sequencing facility or company.
Libraries and library prep (cont.)
After library prep, each DNA fragment is flanked by several types of short sequences that together make up the “adapters”:
Multiplexing!
Adapters can include so-called “indices” or “barcodes” that identify individual samples. That way, up to 96 samples can be combined (multiplexed) into a single library,
i.e. into a single tube.
Paired-end vs. single-end sequencing
DNA fragments can be sequenced from both ends as shown below —
this is called “paired-end” (PE) sequencing:
When sequencing is instead single-end (SE), no reverse read is produced:
Insert size
- The total size of the biological DNA fragment (without adapters) is often called the insert size:
Insert size variation
The insert size can vary – by design, but also because of limited precision in size selection. In some cases, it is:
Shorter than the combined read length, which leads to?
Overlapping reads (this can be useful!):
Shorter than the single read length, which leads to?
“Adapter read-through”: the final bases in the resulting reads will consist of adapter sequence, which should be removed before downstream analysis
How Illumina sequencing works
First, library fragments bind to a surface thanks to the adapters, and the DNA templates are then PCR-amplified to form “clusters” of identical fragments:
In the diagram above, for illustrative purposes:
- Only a few nucleotides are shown (1 block = 1 nucleotide) — in reality, fragments are much longer
- Only two templates and clusters are shown — in reality, there are millions
How Illumina sequencing works (cont.)
Then, sequencing is performed by synthesizing a new strand using fluorescently-labeled bases and taking a picture each time a new nucleotide is incorporated:
How Illumina sequencing works (cont.)
How errors come about in Illumina
- The different templates within a cluster get out of sync because occasionally:
- They miss a base incorporation
- They incorporate two bases at once
- Base incorporation may also terminate before the end of the template is reached
This error profile is why, for Illumina:
- There are hard limits on read lengths
- Base quality scores typically decrease towards the end of the reads
How Illumina sequencing works: Zooming out
How Illumina sequencing works: Zooming out
Nanopore sequencing
A single strand of DNA passes through a nanopore —
the electrical current is measured, which depends on the combination of bases passes in the pore:
ONT (Nanopore) sequencers
Under development!
ONT constantly releases new flow cells with updated technology, which have led to large decreases in error rates over the past decade — and even over the past two or so years.
Genome size variation
Genome structure
https://en.wikipedi.org/wiki/Karyotype
Key features:
- Number of distinct chromosomes
- Ploidy
Growth of genome databases
Konkel and Slot (2023)
The Garrigós et al. 2025 dataset
The labs this and next week are organized around the data set from Garrigós et al. (2025):
This paper uses paired-end Illumina RNA-Seq data to study gene expression in Culex pipiens mosquitos infected with two different malaria-causing Plasmodium protozoans.
